1. Technical Field
The present invention relates to an improved data processing system. In particular, the present invention relates to expressing high availability cluster demand. Still more particularly, the present invention relates to expressing high availability cluster demand based on probability of breach.
2. Description of Related Art
In a large data center, High Availability (H/A) clusters are often used to ensure that servers are available to meet business needs. A H/A cluster is designed, implemented, and deployed with sufficient components to satisfy the functional requirements but which also has sufficient redundancy in components (hardware, software and procedures) to mask certain defined faults. When using H/A clusters, it is desirable to minimize server downtime and to reduce business losses due to system errors. Currently, there are a few software products in the market that provide such functions and features. Examples of these software products include Veritas™ clustering server available from Veritas™ Software Corporation and High Availability Cluster Multiprocessing for AIX 5L V5.2.0 available from International Business Machines Corporation.
However, with existing H/A clusters, a problem exists when more resources are needed while there are no more redundant or standby resources available. One problem scenario occurs when there are two servers running in a H/A cluster. One server is active and the other server is standing by. When the active server fails, the clustering software is capable of failing over all resources to the standby server and making the standby server active. However, if the standby server also fails and there are no more resources available in the cluster, the H/A cluster can no longer provision resources to serve the client requests.
Another problem scenario is when a poisoning problem is detected. A poisoning problem occurs when the servers in the cluster keep failing no matter how many resources are added to the cluster. This poisoning problem may be caused by software errors, for example, memory leaks, software bugs, etc. When a poisoning problem is detected, the cluster notifies the administrator to fix the problem manually. However, it is often difficult for the cluster to detect the problem. Usually, a provisioning manager server, which provisions and de-provisions resources, predicts how and when the poisoning problem may occur.
Therefore, it would be advantageous to have an improved method, apparatus, and computer instructions for expressing high availability demand cluster to a provisioning manager server, such that based on a probability of breach data, the provisioning manager server may respond to the problem accordingly.